---
id: model-configuration
sidebar_label: Overview
title: Model Configuration
description: Learn about model configuration for Rasa Open Source.
abstract: The configuration file defines the components and policies that your model will use to make predictions based on user input.
---

The language and pipeline keys specify the [components](./components.mdx) used by the  model to make NLU predictions.
The policies key defines the [policies](./policies.mdx) used by the model to predict the next action.

If you don't know which components or policies to choose, you can use the
the [Suggested Config](./model-configuration.mdx#suggested-config) feature, which will recommend sensible defaults.

## Suggested Config

You can leave the pipeline and/or policies key out of your configuration file.
When you run `rasa train`, the Suggested Config feature will select a default configuration
for the missing key(s) to train the model.

Make sure to specify the language key in your `config.yml` file with the
2-letter ISO language code.

Example `config.yml` file:

```yaml-rasa (docs/sources/data/configs_for_docs/example_for_suggested_config.yml)
```

The selected configuration will also be written as comments into the `config.yml` file,
so you can see which configuration was used. For the example above, the resulting file
might look e.g. like this:

```yaml-rasa (docs/sources/data/configs_for_docs/example_for_suggested_config_after_train.yml)
```

If you like, you can then un-comment the suggested configuration for one or both of the
keys and make modifications. Note that this will disable automatic suggestions for this
key when training again.
As long as you leave the configuration commented out and don't specify any configuration
for a key yourself, a default configuration will be suggested whenever you train a new
model.

:::note nlu- or dialogue- only models

Only the default configuration for `pipeline` will be automatically selected
if you run `rasa train nlu`, and only the default configuration for `policies`
will be selected if you run `rasa train core`.
:::
